Industries > Telecommunications

Transform Your Data Into Insights and Analytics

Telecom companies have access to a large amount of data which can be transported and captured in order to better their performance. But with the use of sincere analysis and understanding of the given data, there is a way to present deeper insights on customer through processes. It is only recently that this data began being valued and used. Before, it was hard to analyze and store all this information, but as companies have evolved, there is easier ways to deal with such a large influx of data. The mixture of big data technologies and streaming analytics help telecommunications companies to discover very beneficial insight to their customers. This can help people lead to large shifts in the ways they do business.

Call Blocking and Labeling Visibility and Control

Everyday consumers are targeted with unsolicited calls. These often include the calls originated by Robo callers. Telco’s often implementing call blocking techniques to stop these unwanted calls, however with the fraudulent robot callers use the technologies to spoof their caller identity and scam victims with threats from the IRS, offers of loans, or free travel, etc. A comprehensive solution is required to help FCC Robocall Strike Force with call blocking and labeling solution not only help stop fraudulent actors from delivering annoying, illegal and unwanted calls to consumers, address FCC, but also help with the unintended drop-in contact rates for legal call originators around the world

Success Story:

Artha enabled Numeracle to address the problem of improper call blocking and labeling and lack of trust in voice communications

Fraud Detection

The telecommunication industry is very vulnerable to fraudulent activity due to its high traffic of customers and users. The most widespread fraud in the telecom area is illegal access and authorization, fake profiles, behavioral fraud, etc. There is a very apparent direct relationship between company and customer in terms of fraud.

Predictive Analytics

Telecommunication companies use predictive analytics in order to gather the information that will ease decision making. To better understand the customer, organizations should have knowledge about customers preferences and needs. Predictive analytics analyzes past and current data to predict the future, the better is the quality of historical data, the better is predictability.


Customer Segmentation

Segmenting the market and pinpointing each groups content helps companies to stay relevant. This golden rule is relevant to the various areas of business.

There are four segmentation schemes of primary importance:

  • Customer value segmentation
  • Customer behavior segmentation
  • Customer lifecycle segmentation
  • Customer migration segmentation

Accurately targeting markets helps with identifying customer needs in order to enhance business performance. It enables enhanced business planning and targeting.

Network Management and Optimization

When customers seem to feel more engaged and interested in the functions being offered, there is a higher chance of a successful partnership for telecommunication companies. To better understand these complications and its root cause network optimization and management gains an advantage in the operations. By analyzing trends displayed in older data, people can help prevent problems and help benefit sales and business in the future.


Case Study
Implementation of Data Lake to perform cognitive analytics on Telecom customers
Case Study
Learn how Artha assisted Asian telecom giants on their digital transformation journey
Case Study
Data Science Analytics - Recommendation engine to attracts new customers using R

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